Barbara Oberbauer
@barbaraoberbauer.bsky.social
PhD student @cmdn-lab.bsky.social (PI: @sgluth.bsky.social) at the University of Hamburg modeling dietary and sustainable decision-making - ScieCom enthusiast - all about soccer, rowing, and books 📚
Github: https://github.com/barbaraoberbauer
Github: https://github.com/barbaraoberbauer
Taken together, we provide novel insights into how attribute translations lead to behavior change and how behaviorally effective translations in the form of ratings differ from less effective numeric translations.
September 11, 2025 at 5:30 AM
Taken together, we provide novel insights into how attribute translations lead to behavior change and how behaviorally effective translations in the form of ratings differ from less effective numeric translations.
In contrast, we found only response deliberation to increase for behaviorally less effective numeric translations (carbon emissions in kg).
September 8, 2025 at 7:32 AM
In contrast, we found only response deliberation to increase for behaviorally less effective numeric translations (carbon emissions in kg).
Our modeling results suggest that a translation in form of an evaluative rating caused participants to make more ecological choices as a result of a shift in attribute weights in favor of the translated attribute, a decreased attentional bias on the attended option, and increased deliberation.
September 8, 2025 at 7:32 AM
Our modeling results suggest that a translation in form of an evaluative rating caused participants to make more ecological choices as a result of a shift in attribute weights in favor of the translated attribute, a decreased attentional bias on the attended option, and increased deliberation.
To fill this gap, we model the interplay of attention and evidence accumulation using the maaDDM for a pre-existing data set from an online process tracing study in which participants completed a consumer choice task w/ and w/o the translation of the items' energy and water consumption.
September 8, 2025 at 7:32 AM
To fill this gap, we model the interplay of attention and evidence accumulation using the maaDDM for a pre-existing data set from an online process tracing study in which participants completed a consumer choice task w/ and w/o the translation of the items' energy and water consumption.
Attribute translations promote behavior change by translating decision-relevant information into more meaningful units and have been widely adopted by policy makers (e.g., EU energy label). However, little is known about the computational mechanisms that underlie their effects on behavior.
September 8, 2025 at 7:32 AM
Attribute translations promote behavior change by translating decision-relevant information into more meaningful units and have been widely adopted by policy makers (e.g., EU energy label). However, little is known about the computational mechanisms that underlie their effects on behavior.
Our modeling results suggest that a translation in form of an evaluative rating caused participants to make more ecological choices as a result of a shift in attribute weights in favor of the translated attribute, a decreased attentional bias on the attended option, and increased deliberation.
September 8, 2025 at 7:24 AM
Our modeling results suggest that a translation in form of an evaluative rating caused participants to make more ecological choices as a result of a shift in attribute weights in favor of the translated attribute, a decreased attentional bias on the attended option, and increased deliberation.
To fill this gap, we model the interplay of attention and evidence accumulation using the maaDDM for a pre-existing data set from an online process tracing study in which participants completed a consumer choice task w/ and w/o the translation of the items' energy and water consumption.
September 8, 2025 at 7:24 AM
To fill this gap, we model the interplay of attention and evidence accumulation using the maaDDM for a pre-existing data set from an online process tracing study in which participants completed a consumer choice task w/ and w/o the translation of the items' energy and water consumption.
Attribute translations promote behavior change by translating decision-relevant information into more meaningful units and have been widely adopted by policy makers (e.g., EU energy label). However, little is known about the computational mechanisms that underlie their effects on behavior.
September 8, 2025 at 7:24 AM
Attribute translations promote behavior change by translating decision-relevant information into more meaningful units and have been widely adopted by policy makers (e.g., EU energy label). However, little is known about the computational mechanisms that underlie their effects on behavior.